{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.699735600Z",
     "start_time": "2023-11-27T11:40:24.136838800Z"
    }
   },
   "outputs": [],
   "source": [
    "import pandas as pd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.701186300Z",
     "start_time": "2023-11-27T11:40:24.232371100Z"
    }
   },
   "outputs": [],
   "source": [
    "import pickle\n",
    "with open('AMZN.pkl','rb') as f:\n",
    "    amzn=pickle.load(f)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.703325Z",
     "start_time": "2023-11-27T11:40:24.261730Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "           date         Open      High       Low     Close      Volume  \\\n0    2002-01-02    10.930000  1.006404  0.958829  1.002745   6519600.0   \n1    2002-01-03    11.130000  1.072776  0.992812  1.069182  10875700.0   \n2    2002-01-04    12.020000  1.031614  0.994176  1.019135  12687300.0   \n3    2002-01-07    12.080000  1.035596  1.000000  1.021523  12182900.0   \n4    2002-01-08    12.270000  1.004075  0.957620  0.965770   6041100.0   \n...         ...          ...       ...       ...       ...         ...   \n5045 2022-01-14  3203.000000  1.013113  0.997818  1.012413   2295800.0   \n5046 2022-01-18  3182.100098  1.003956  0.990946  0.998822   3364600.0   \n5047 2022-01-19  3175.239990  1.003074  0.984178  0.984486   2662100.0   \n5048 2022-01-20  3135.320068  1.007872  0.965458  0.967477   3598700.0   \n5049 2022-01-21  2999.000000  1.006335  0.947452  0.951270   8164200.0   \n\n            ATR         CCI       CSI  demand_index       DMI          EMA  \\\n0      0.844975  -43.495283  0.934190      0.065294  1.103441    10.770119   \n1      0.853977   60.759179  0.994657      0.573208  0.942893    10.920770   \n2      0.830378  117.235915  1.018426      0.488334  1.357515    11.098001   \n3      0.803687  114.755444  1.040965      0.579182  0.993931    11.263600   \n4      0.789441   73.215505  1.016821     -0.931448  0.796020    11.341787   \n...         ...         ...       ...           ...       ...          ...   \n5045  81.050068 -136.852686  1.013420      0.929643  1.210694  3303.651657   \n5046  81.611395 -166.501387  1.063655     -0.082209  0.823110  3286.944782   \n5047  80.170635 -168.645091  1.058476     -0.955773  0.214685  3265.482809   \n5048  83.691258 -200.087263  1.082688     -0.492674  0.709083  3234.531781   \n5049  90.907853 -268.015726  1.109742     -0.392529  0.753587  3183.642224   \n\n              HMA         MOM  \n0       10.376372    0.150000  \n1       10.615454    1.040000  \n2       10.957697    1.540000  \n3       11.358919    2.190001  \n4       11.703387    1.850000  \n...           ...         ...  \n5045  3238.615246  -91.580078  \n5046  3222.198667 -229.739990  \n5047  3198.651270 -224.459961  \n5048  3163.987134 -253.789795  \n5049  3104.793426 -412.219971  \n\n[5050 rows x 14 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>Open</th>\n      <th>High</th>\n      <th>Low</th>\n      <th>Close</th>\n      <th>Volume</th>\n      <th>ATR</th>\n      <th>CCI</th>\n      <th>CSI</th>\n      <th>demand_index</th>\n      <th>DMI</th>\n      <th>EMA</th>\n      <th>HMA</th>\n      <th>MOM</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>0</th>\n      <td>2002-01-02</td>\n      <td>10.930000</td>\n      <td>1.006404</td>\n      <td>0.958829</td>\n      <td>1.002745</td>\n      <td>6519600.0</td>\n      <td>0.844975</td>\n      <td>-43.495283</td>\n      <td>0.934190</td>\n      <td>0.065294</td>\n      <td>1.103441</td>\n      <td>10.770119</td>\n      <td>10.376372</td>\n      <td>0.150000</td>\n    </tr>\n    <tr>\n      <th>1</th>\n      <td>2002-01-03</td>\n      <td>11.130000</td>\n      <td>1.072776</td>\n      <td>0.992812</td>\n      <td>1.069182</td>\n      <td>10875700.0</td>\n      <td>0.853977</td>\n      <td>60.759179</td>\n      <td>0.994657</td>\n      <td>0.573208</td>\n      <td>0.942893</td>\n      <td>10.920770</td>\n      <td>10.615454</td>\n      <td>1.040000</td>\n    </tr>\n    <tr>\n      <th>2</th>\n      <td>2002-01-04</td>\n      <td>12.020000</td>\n      <td>1.031614</td>\n      <td>0.994176</td>\n      <td>1.019135</td>\n      <td>12687300.0</td>\n      <td>0.830378</td>\n      <td>117.235915</td>\n      <td>1.018426</td>\n      <td>0.488334</td>\n      <td>1.357515</td>\n      <td>11.098001</td>\n      <td>10.957697</td>\n      <td>1.540000</td>\n    </tr>\n    <tr>\n      <th>3</th>\n      <td>2002-01-07</td>\n      <td>12.080000</td>\n      <td>1.035596</td>\n      <td>1.000000</td>\n      <td>1.021523</td>\n      <td>12182900.0</td>\n      <td>0.803687</td>\n      <td>114.755444</td>\n      <td>1.040965</td>\n      <td>0.579182</td>\n      <td>0.993931</td>\n      <td>11.263600</td>\n      <td>11.358919</td>\n      <td>2.190001</td>\n    </tr>\n    <tr>\n      <th>4</th>\n      <td>2002-01-08</td>\n      <td>12.270000</td>\n      <td>1.004075</td>\n      <td>0.957620</td>\n      <td>0.965770</td>\n      <td>6041100.0</td>\n      <td>0.789441</td>\n      <td>73.215505</td>\n      <td>1.016821</td>\n      <td>-0.931448</td>\n      <td>0.796020</td>\n      <td>11.341787</td>\n      <td>11.703387</td>\n      <td>1.850000</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>5045</th>\n      <td>2022-01-14</td>\n      <td>3203.000000</td>\n      <td>1.013113</td>\n      <td>0.997818</td>\n      <td>1.012413</td>\n      <td>2295800.0</td>\n      <td>81.050068</td>\n      <td>-136.852686</td>\n      <td>1.013420</td>\n      <td>0.929643</td>\n      <td>1.210694</td>\n      <td>3303.651657</td>\n      <td>3238.615246</td>\n      <td>-91.580078</td>\n    </tr>\n    <tr>\n      <th>5046</th>\n      <td>2022-01-18</td>\n      <td>3182.100098</td>\n      <td>1.003956</td>\n      <td>0.990946</td>\n      <td>0.998822</td>\n      <td>3364600.0</td>\n      <td>81.611395</td>\n      <td>-166.501387</td>\n      <td>1.063655</td>\n      <td>-0.082209</td>\n      <td>0.823110</td>\n      <td>3286.944782</td>\n      <td>3222.198667</td>\n      <td>-229.739990</td>\n    </tr>\n    <tr>\n      <th>5047</th>\n      <td>2022-01-19</td>\n      <td>3175.239990</td>\n      <td>1.003074</td>\n      <td>0.984178</td>\n      <td>0.984486</td>\n      <td>2662100.0</td>\n      <td>80.170635</td>\n      <td>-168.645091</td>\n      <td>1.058476</td>\n      <td>-0.955773</td>\n      <td>0.214685</td>\n      <td>3265.482809</td>\n      <td>3198.651270</td>\n      <td>-224.459961</td>\n    </tr>\n    <tr>\n      <th>5048</th>\n      <td>2022-01-20</td>\n      <td>3135.320068</td>\n      <td>1.007872</td>\n      <td>0.965458</td>\n      <td>0.967477</td>\n      <td>3598700.0</td>\n      <td>83.691258</td>\n      <td>-200.087263</td>\n      <td>1.082688</td>\n      <td>-0.492674</td>\n      <td>0.709083</td>\n      <td>3234.531781</td>\n      <td>3163.987134</td>\n      <td>-253.789795</td>\n    </tr>\n    <tr>\n      <th>5049</th>\n      <td>2022-01-21</td>\n      <td>2999.000000</td>\n      <td>1.006335</td>\n      <td>0.947452</td>\n      <td>0.951270</td>\n      <td>8164200.0</td>\n      <td>90.907853</td>\n      <td>-268.015726</td>\n      <td>1.109742</td>\n      <td>-0.392529</td>\n      <td>0.753587</td>\n      <td>3183.642224</td>\n      <td>3104.793426</td>\n      <td>-412.219971</td>\n    </tr>\n  </tbody>\n</table>\n<p>5050 rows × 14 columns</p>\n</div>"
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "amzn"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.959228500Z",
     "start_time": "2023-11-27T11:40:24.304500300Z"
    }
   },
   "outputs": [],
   "source": [
    "csi=pd.read_csv('nas_fea.csv')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.960228900Z",
     "start_time": "2023-11-27T11:40:24.803668900Z"
    }
   },
   "outputs": [],
   "source": [
    "stockunique=csi['stockcode'].unique()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.979359600Z",
     "start_time": "2023-11-27T11:40:24.815635400Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "array(['AAL', 'AAPL', 'ADBE', 'ADI', 'ADP', 'ADSK', 'ALGN', 'AMAT', 'AMD',\n       'AMGN', 'AMZN', 'ASML', 'ATVI', 'AVGO', 'BIDU', 'BIIB', 'BKNG',\n       'BMRN', 'CDNS', 'CDW', 'CHKP', 'CHTR', 'CMCSA', 'COST', 'CSCO',\n       'CSX', 'CTAS', 'CTSH', 'DLTR', 'EA', 'EBAY', 'EXPE', 'FAST',\n       'FISV', 'GILD', 'GOOGL', 'HAS', 'HSIC', 'IDXX', 'ILMN', 'INCY',\n       'INTC', 'ISRG', 'JBHT', 'JD', 'KHC', 'KLAC', 'LBTYK', 'LRCX',\n       'LULU', 'MAR', 'MCHP', 'MDLZ', 'MELI', 'MNST', 'MSFT', 'MU',\n       'NFLX', 'NTAP', 'NTES', 'NVDA', 'NXPI', 'ORLY', 'PAYX', 'PCAR',\n       'PEP', 'PYPL', 'QCOM', 'REGN', 'ROST', 'SBUX', 'SIRI', 'SNPS',\n       'SWKS', 'TCOM', 'TMUS', 'TSLA', 'TTWO', 'TXN', 'UAL', 'ULTA',\n       'VRSK', 'VRSN', 'VRTX', 'WBA', 'WDAY', 'WDC', 'WYNN', 'XEL',\n       'FOXA'], dtype=object)"
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "stockunique"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.980685100Z",
     "start_time": "2023-11-27T11:40:24.831617600Z"
    }
   },
   "outputs": [],
   "source": [
    "csi=csi[(csi['date']<'2022')&(csi['date']>='2019-04-09')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.981770500Z",
     "start_time": "2023-11-27T11:40:24.879835800Z"
    }
   },
   "outputs": [],
   "source": [
    "csi.reset_index(inplace=True,drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.981770500Z",
     "start_time": "2023-11-27T11:40:24.892246400Z"
    }
   },
   "outputs": [],
   "source": [
    "csi.to_pickle('E:/baselines/THGNN/nas90fealab.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.982847600Z",
     "start_time": "2023-11-27T11:40:24.926676500Z"
    }
   },
   "outputs": [],
   "source": [
    "df=csi[(csi['date']>='2020')&(csi['date']<='2022')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:24.992061400Z",
     "start_time": "2023-11-27T11:40:24.954229300Z"
    }
   },
   "outputs": [],
   "source": [
    "csi.rename(columns={'date':'dt','stockcode':'kdcode'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.053808400Z",
     "start_time": "2023-11-27T11:40:24.971992400Z"
    }
   },
   "outputs": [],
   "source": [
    "csi.rename(columns={'dt':'datetime','kdcode':'instrument'},inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.117892600Z",
     "start_time": "2023-11-27T11:40:24.985983700Z"
    }
   },
   "outputs": [],
   "source": [
    "fea=csi[['datetime','instrument','open','close','low','open','adjcp','volume']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.118920400Z",
     "start_time": "2023-11-27T11:40:25.025796300Z"
    }
   },
   "outputs": [],
   "source": [
    "lab=csi[['datetime','instrument','label']]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.150710800Z",
     "start_time": "2023-11-27T11:40:25.052808800Z"
    }
   },
   "outputs": [],
   "source": [
    "lab.set_index(['datetime','instrument'],inplace=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.174163600Z",
     "start_time": "2023-11-27T11:40:25.080667700Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "                          label\ndatetime   instrument          \n2019-04-09 AAL         1.021315\n           AAPL        1.005614\n           ADBE        1.009629\n           ADI         1.014300\n           ADP         1.004634\n...                         ...\n2021-12-31 WBA         1.017255\n           WDAY        0.965371\n           WDC         1.011041\n           WYNN        1.032102\n           XEL         1.003545\n\n[62100 rows x 1 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th></th>\n      <th>label</th>\n    </tr>\n    <tr>\n      <th>datetime</th>\n      <th>instrument</th>\n      <th></th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">2019-04-09</th>\n      <th>AAL</th>\n      <td>1.021315</td>\n    </tr>\n    <tr>\n      <th>AAPL</th>\n      <td>1.005614</td>\n    </tr>\n    <tr>\n      <th>ADBE</th>\n      <td>1.009629</td>\n    </tr>\n    <tr>\n      <th>ADI</th>\n      <td>1.014300</td>\n    </tr>\n    <tr>\n      <th>ADP</th>\n      <td>1.004634</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <th>...</th>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th rowspan=\"5\" valign=\"top\">2021-12-31</th>\n      <th>WBA</th>\n      <td>1.017255</td>\n    </tr>\n    <tr>\n      <th>WDAY</th>\n      <td>0.965371</td>\n    </tr>\n    <tr>\n      <th>WDC</th>\n      <td>1.011041</td>\n    </tr>\n    <tr>\n      <th>WYNN</th>\n      <td>1.032102</td>\n    </tr>\n    <tr>\n      <th>XEL</th>\n      <td>1.003545</td>\n    </tr>\n  </tbody>\n</table>\n<p>62100 rows × 1 columns</p>\n</div>"
     },
     "execution_count": 47,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "lab"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.176266200Z",
     "start_time": "2023-11-27T11:40:25.116851700Z"
    }
   },
   "outputs": [],
   "source": [
    "lab.to_pickle('E:/baselines/TRA/data/nas90lab.pkl')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.212791400Z",
     "start_time": "2023-11-27T11:40:25.128954500Z"
    }
   },
   "outputs": [],
   "source": [
    "df.reset_index(inplace=True,drop=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.215965100Z",
     "start_time": "2023-11-27T11:40:25.159461400Z"
    }
   },
   "outputs": [],
   "source": [
    "index = df[df['date'].ge('2021-05-22')].index[0] // 255"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.303792100Z",
     "start_time": "2023-11-27T11:40:25.189171300Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "             date      open      high       low     close     adjcp    volume  \\\n31500  2021-05-24  0.017258  0.017014  0.017351  0.017183  0.017498  0.190783   \n31501  2021-05-24  0.113647  0.113738  0.115891  0.113624  0.112562  0.460151   \n31502  2021-05-24  0.458081  0.456823  0.464117  0.457042  0.457301  0.013466   \n31503  2021-05-24  0.146331  0.146059  0.148985  0.146425  0.141450  0.025045   \n31504  2021-05-24  0.179472  0.178666  0.182707  0.178411  0.171865  0.008991   \n...           ...       ...       ...       ...       ...       ...       ...   \n45445  2021-12-31  0.044401  0.044097  0.045394  0.044205  0.041776  0.024842   \n45446  2021-12-31  0.253343  0.251461  0.255592  0.248942  0.249227  0.005497   \n45447  2021-12-31  0.056949  0.056712  0.058084  0.056293  0.056602  0.013543   \n45448  2021-12-31  0.075805  0.075837  0.076842  0.074662  0.074969  0.017545   \n45449  2021-12-31  0.058921  0.058446  0.059273  0.058600  0.056723  0.041601   \n\n      stockcode       pos       neg     ret_1     label  \n31500       AAL  0.877836  0.122164  1.018609  1.009569  \n31501      AAPL  0.741952  0.258048  1.013314  0.998426  \n31502      ADBE  0.696971  0.303029  1.019997  1.014563  \n31503       ADI  0.500000  0.500000  1.019767  1.007446  \n31504       ADP  0.500000  0.500000  1.009013  0.990662  \n...         ...       ...       ...       ...       ...  \n45445       WBA  0.500000  0.500000  1.003270  1.017255  \n45446      WDAY  0.500000  0.500000  0.987993  0.965371  \n45447       WDC  0.783497  0.216503  0.997552  1.011041  \n45448      WYNN  0.500000  0.500000  0.987115  1.032102  \n45449       XEL  0.500000  0.500000  0.992232  1.003545  \n\n[13950 rows x 12 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>open</th>\n      <th>high</th>\n      <th>low</th>\n      <th>close</th>\n      <th>adjcp</th>\n      <th>volume</th>\n      <th>stockcode</th>\n      <th>pos</th>\n      <th>neg</th>\n      <th>ret_1</th>\n      <th>label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>31500</th>\n      <td>2021-05-24</td>\n      <td>0.017258</td>\n      <td>0.017014</td>\n      <td>0.017351</td>\n      <td>0.017183</td>\n      <td>0.017498</td>\n      <td>0.190783</td>\n      <td>AAL</td>\n      <td>0.877836</td>\n      <td>0.122164</td>\n      <td>1.018609</td>\n      <td>1.009569</td>\n    </tr>\n    <tr>\n      <th>31501</th>\n      <td>2021-05-24</td>\n      <td>0.113647</td>\n      <td>0.113738</td>\n      <td>0.115891</td>\n      <td>0.113624</td>\n      <td>0.112562</td>\n      <td>0.460151</td>\n      <td>AAPL</td>\n      <td>0.741952</td>\n      <td>0.258048</td>\n      <td>1.013314</td>\n      <td>0.998426</td>\n    </tr>\n    <tr>\n      <th>31502</th>\n      <td>2021-05-24</td>\n      <td>0.458081</td>\n      <td>0.456823</td>\n      <td>0.464117</td>\n      <td>0.457042</td>\n      <td>0.457301</td>\n      <td>0.013466</td>\n      <td>ADBE</td>\n      <td>0.696971</td>\n      <td>0.303029</td>\n      <td>1.019997</td>\n      <td>1.014563</td>\n    </tr>\n    <tr>\n      <th>31503</th>\n      <td>2021-05-24</td>\n      <td>0.146331</td>\n      <td>0.146059</td>\n      <td>0.148985</td>\n      <td>0.146425</td>\n      <td>0.141450</td>\n      <td>0.025045</td>\n      <td>ADI</td>\n      <td>0.500000</td>\n      <td>0.500000</td>\n      <td>1.019767</td>\n      <td>1.007446</td>\n    </tr>\n    <tr>\n      <th>31504</th>\n      <td>2021-05-24</td>\n      <td>0.179472</td>\n      <td>0.178666</td>\n      <td>0.182707</td>\n      <td>0.178411</td>\n      <td>0.171865</td>\n      <td>0.008991</td>\n      <td>ADP</td>\n      <td>0.500000</td>\n      <td>0.500000</td>\n      <td>1.009013</td>\n      <td>0.990662</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>45445</th>\n      <td>2021-12-31</td>\n      <td>0.044401</td>\n      <td>0.044097</td>\n      <td>0.045394</td>\n      <td>0.044205</td>\n      <td>0.041776</td>\n      <td>0.024842</td>\n      <td>WBA</td>\n      <td>0.500000</td>\n      <td>0.500000</td>\n      <td>1.003270</td>\n      <td>1.017255</td>\n    </tr>\n    <tr>\n      <th>45446</th>\n      <td>2021-12-31</td>\n      <td>0.253343</td>\n      <td>0.251461</td>\n      <td>0.255592</td>\n      <td>0.248942</td>\n      <td>0.249227</td>\n      <td>0.005497</td>\n      <td>WDAY</td>\n      <td>0.500000</td>\n      <td>0.500000</td>\n      <td>0.987993</td>\n      <td>0.965371</td>\n    </tr>\n    <tr>\n      <th>45447</th>\n      <td>2021-12-31</td>\n      <td>0.056949</td>\n      <td>0.056712</td>\n      <td>0.058084</td>\n      <td>0.056293</td>\n      <td>0.056602</td>\n      <td>0.013543</td>\n      <td>WDC</td>\n      <td>0.783497</td>\n      <td>0.216503</td>\n      <td>0.997552</td>\n      <td>1.011041</td>\n    </tr>\n    <tr>\n      <th>45448</th>\n      <td>2021-12-31</td>\n      <td>0.075805</td>\n      <td>0.075837</td>\n      <td>0.076842</td>\n      <td>0.074662</td>\n      <td>0.074969</td>\n      <td>0.017545</td>\n      <td>WYNN</td>\n      <td>0.500000</td>\n      <td>0.500000</td>\n      <td>0.987115</td>\n      <td>1.032102</td>\n    </tr>\n    <tr>\n      <th>45449</th>\n      <td>2021-12-31</td>\n      <td>0.058921</td>\n      <td>0.058446</td>\n      <td>0.059273</td>\n      <td>0.058600</td>\n      <td>0.056723</td>\n      <td>0.041601</td>\n      <td>XEL</td>\n      <td>0.500000</td>\n      <td>0.500000</td>\n      <td>0.992232</td>\n      <td>1.003545</td>\n    </tr>\n  </tbody>\n</table>\n<p>13950 rows × 12 columns</p>\n</div>"
     },
     "execution_count": 51,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df[df['date'].ge('2021-05-22')]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.330466600Z",
     "start_time": "2023-11-27T11:40:25.220236Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "123"
     },
     "execution_count": 52,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "index"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.415887200Z",
     "start_time": "2023-11-27T11:40:25.233842700Z"
    }
   },
   "outputs": [],
   "source": [
    "df=df.groupby('date')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.647947500Z",
     "start_time": "2023-11-27T11:40:25.249934900Z"
    }
   },
   "outputs": [
    {
     "data": {
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0.128335419, ..., 0.5, 1.006273787,\n         0.995796805],\n        ['2020-01-08', 0.054389263, 0.053521502, ..., 0.5, 0.999039424,\n         1.00224358]], dtype=object),\n array([['2020-01-09', 0.022153744, 0.02179037, ..., 0.09710079,\n         1.003951171, 0.977459712],\n        ['2020-01-09', 0.067675901, 0.06732376, ..., 0.36028734,\n         1.021240814, 1.002260704],\n        ['2020-01-09', 0.313721693, 0.310957714, ..., 0.116542466,\n         1.007636124, 0.998120092],\n        ...,\n        ['2020-01-09', 0.06074293, 0.060004205, ..., 0.5, 0.999708674,\n         0.990090349],\n        ['2020-01-09', 0.130212816, 0.128427626, ..., 0.1645245,\n         0.995796805, 1.006049952],\n        ['2020-01-09', 0.053978145, 0.053632159, ..., 0.5, 1.00224358,\n         1.001598952]], dtype=object),\n array([['2020-01-10', 0.022032276, 0.021569055, ..., 0.08784747,\n         0.977459712, 1.002562214],\n        ['2020-01-10', 0.068460769, 0.067840168, ..., 0.24075554,\n         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array([['2020-01-17', 0.022349959, 0.022242223, ..., 0.5, 1.006021965,\n         0.957746519],\n        ['2020-01-17', 0.069785225, 0.069239523, ..., 0.27734458,\n         1.011070996, 0.993223093],\n        ['2020-01-17', 0.322000134, 0.318464017, ..., 0.416788,\n         1.012623734, 1.000743437],\n        ...,\n        ['2020-01-17', 0.061088647, 0.060124089, ..., 0.5, 0.994029474,\n         1.007764412],\n        ['2020-01-17', 0.13857536, 0.137224931, ..., 0.5, 0.9961237,\n         0.938596505],\n        ['2020-01-17', 0.056790579, 0.056140408, ..., 0.5, 1.005228417,\n         1.009637406]], dtype=object),\n array([['2020-01-21', 0.02204162, 0.021569055, ..., 0.27679637,\n         0.957746519, 1.004411725],\n        ['2020-01-21', 0.070000131, 0.069304073, ..., 0.25122172,\n         0.993223093, 1.003569526],\n        ['2020-01-21', 0.319542756, 0.320695601, ..., 0.123094305,\n         1.000743437, 1.000171422],\n        ...,\n        ['2020-01-21', 0.05904239, 0.059377144, ..., 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0.07356239, 0.072443995, ..., 0.5, 0.992678821,\n         0.974005543],\n        ['2021-12-15', 0.059126486, 0.059275707, ..., 0.5, 1.02121977,\n         1.001888946]], dtype=object),\n array([['2021-12-16', 0.01202525, 0.01179428, ..., 0.16268672,\n         0.972336709, 1.026029073],\n        ['2021-12-16', 0.163420066, 0.162796107, ..., 0.068406954,\n         0.960736149, 0.993498229],\n        ['2021-12-16', 0.536343001, 0.541282779, ..., 0.2038981,\n         0.898085148, 0.983306521],\n        ...,\n        ['2021-12-16', 0.049007334, 0.049399497, ..., 0.17176722,\n         1.006388653, 1.00246869],\n        ['2021-12-16', 0.073917445, 0.073190933, ..., 0.5, 0.974005543,\n         1.021226404],\n        ['2021-12-16', 0.059986098, 0.059911992, ..., 0.5, 1.001888946,\n         0.97171868]], dtype=object),\n array([['2021-12-17', 0.011473976, 0.011711286, ..., 0.16068736,\n         1.026029073, 1.020648877],\n        ['2021-12-17', 0.154683767, 0.155723229, ..., 0.119700685,\n         0.993498229, 0.991877998],\n        ['2021-12-17', 0.524840996, 0.518607121, ..., 0.18989642,\n         0.983306521, 0.987658101],\n        ...,\n        ['2021-12-17', 0.048773744, 0.048818546, ..., 0.5, 1.00246869,\n         0.983289411],\n        ['2021-12-17', 0.070189339, 0.071881483, ..., 0.5, 1.021226404,\n         0.982010505],\n        ['2021-12-17', 0.059761846, 0.059266491, ..., 0.5, 0.97171868,\n         1.001791086]], dtype=object),\n array([['2021-12-20', 0.011324478, 0.012153919, ..., 0.13286099,\n         1.020648877, 1.047398939],\n        ['2021-12-20', 0.153142074, 0.15305822, ..., 0.76972777,\n         0.991877998, 1.019086925],\n        ['2021-12-20', 0.505705206, 0.509643864, ..., 0.29311574,\n         0.987658101, 1.014096804],\n        ...,\n        ['2021-12-20', 0.048194436, 0.047896397, ..., 0.5, 0.983289411,\n         1.055813933],\n        ['2021-12-20', 0.070703242, 0.071724713, ..., 0.34987777,\n         0.982010505, 1.06844905],\n        ['2021-12-20', 0.057967871, 0.057763384, ..., 0.5, 1.001791086,\n         0.988378928]], dtype=object),\n array([['2021-12-21', 0.012212123, 0.012780978, ..., 0.5, 1.047398939,\n         1.007726235],\n        ['2021-12-21', 0.156206783, 0.155474245, ..., 0.4349794,\n         1.019086925, 1.015318769],\n        ['2021-12-21', 0.510657318, 0.512059889, ..., 0.23758093,\n         1.014096804, 1.011586958],\n        ...,\n        ['2021-12-21', 0.050119225, 0.050210989, ..., 0.5, 1.055813933,\n         1.013046433],\n        ['2021-12-21', 0.072422466, 0.075736065, ..., 0.5, 1.06844905,\n         0.994786875],\n        ['2021-12-21', 0.058547179, 0.057781831, ..., 0.5, 0.988378928,\n         1.005878912]], dtype=object),\n array([['2021-12-22', 0.012894208, 0.012817865, ..., 0.22302456,\n         1.007726235, 1.0],\n        ['2021-12-22', 0.157589636, 0.157927163, ..., 0.1293425,\n         1.015318769, 1.003643813],\n        ['2021-12-22', 0.519430999, 0.516698267, ..., 0.09411062,\n         1.011586958, 1.010000381],\n        ...,\n        ['2021-12-22', 0.051081618, 0.051160804, ..., 0.5, 1.013046433,\n         1.023582536],\n        ['2021-12-22', 0.076169263, 0.076058815, ..., 0.5, 0.994786875,\n         1.035052922],\n        ['2021-12-22', 0.05734185, 0.057486744, ..., 0.5, 1.005878912,\n         0.998201667]], dtype=object),\n array([['2021-12-23', 0.013277297, 0.013020737, ..., 0.36754996, 1.0,\n         0.995071186],\n        ['2021-12-23', 0.160215208, 0.158840096, ..., 0.5522581,\n         1.003643813, 1.02297483],\n        ['2021-12-23', 0.527522613, 0.523752726, ..., 0.15093489,\n         1.010000381, 1.01414978],\n        ...,\n        ['2021-12-23', 0.051969263, 0.052783784, ..., 0.5, 1.023582536,\n         1.014542474],\n        ['2021-12-23', 0.080187019, 0.079203338, ..., 0.13282628,\n         1.035052922, 0.985373588],\n        ['2021-12-23', 0.058322934, 0.057569734, ..., 0.5, 0.998201667,\n         1.003152666]], dtype=object),\n array([['2021-12-27', 0.012408339, 0.012578106, ..., 0.28508547,\n         0.995071186, 1.020363282],\n        ['2021-12-27', 0.161373809, 0.162132159, ..., 0.31860206,\n         1.02297483, 0.994232748],\n        ['2021-12-27', 0.533203499, 0.531415778, ..., 0.19704755,\n         1.01414978, 0.98559755],\n        ...,\n        ['2021-12-27', 0.05342687, 0.053429289, ..., 0.5, 1.014542474,\n         1.01207924],\n        ['2021-12-27', 0.078094048, 0.07690719, ..., 0.5, 0.985373588,\n         0.987211661],\n        ['2021-12-27', 0.058341618, 0.057486744, ..., 0.5, 1.003152666,\n         1.011972509]], dtype=object),\n array([['2021-12-28', 0.012754054, 0.012946965, ..., 0.1442829,\n         1.020363282, 0.973570569],\n        ['2021-12-28', 0.16424231, 0.162971317, ..., 0.2407686,\n         0.994232748, 1.000502045],\n        ['2021-12-28', 0.540491575, 0.533260075, ..., 0.5, 0.98559755,\n         0.999877042],\n        ...,\n        ['2021-12-28', 0.054034204, 0.053798146, ..., 0.52413464,\n         1.01207924, 1.052355142],\n        ['2021-12-28', 0.076823314, 0.077359041, ..., 0.5, 0.987211661,\n         0.982882307],\n        ['2021-12-28', 0.058341618, 0.058123021, ..., 0.5, 1.011972509,\n         1.005028044]], dtype=object),\n array([['2021-12-29', 0.013099767, 0.012753315, ..., 0.13889329,\n         0.973570569, 1.001108059],\n        ['2021-12-29', 0.163466787, 0.162325816, ..., 0.064809084,\n         1.000502045, 0.993421742],\n        ['2021-12-29', 0.531605775, 0.527800971, ..., 0.3169412,\n         0.999877042, 1.002178242],\n        ...,\n        ['2021-12-29', 0.056071116, 0.057763384, ..., 0.5969747,\n         1.052355142, 0.988507568],\n        ['2021-12-29', 0.076337449, 0.075348757, ..., 0.5, 0.982882307,\n         1.013767923],\n        ['2021-12-29', 0.059182546, 0.058537993, ..., 0.5, 1.005028044,\n         1.003972988]], dtype=object),\n array([['2021-12-30', 0.012707335, 0.012707207, ..., 0.23160346,\n         1.001108059, 0.993912528],\n        ['2021-12-30', 0.163597597, 0.162270489, ..., 0.065091394,\n         0.993421742, 0.996464705],\n        ['2021-12-30', 0.529026924, 0.529672904, ..., 0.5, 1.002178242,\n         0.993917881],\n        ...,\n        ['2021-12-30', 0.056977449, 0.057182433, ..., 0.14590777,\n         0.988507568, 0.997552338],\n        ['2021-12-30', 0.075029339, 0.076879527, ..., 0.16059804,\n         1.013767923, 0.987115489],\n        ['2021-12-30', 0.059649727, 0.058731643, ..., 0.5, 1.003972988,\n         0.992232062]], dtype=object),\n array([['2021-12-31', 0.012791427, 0.012688765, ..., 0.2035586,\n         0.993912528, 1.04398669],\n        ['2021-12-31', 0.162308172, 0.1610348, ..., 0.08932803,\n         0.996464705, 1.02500415],\n        ['2021-12-31', 0.52849433, 0.521539547, ..., 0.059411246,\n         0.993917881, 0.99525623],\n        ...,\n        ['2021-12-31', 0.056949419, 0.056712135, ..., 0.21650323,\n         0.997552338, 1.01104127],\n        ['2021-12-31', 0.075804862, 0.075837494, ..., 0.5, 0.987115489,\n         1.032102489],\n        ['2021-12-31', 0.058920925, 0.058445779, ..., 0.5, 0.992232062,\n         1.003545133]], dtype=object)]"
     },
     "execution_count": 54,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "[df.get_group(x).to_numpy() for x in df.groups]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Index(['date', 'open', 'high', 'low', 'close', 'adjcp', 'volume', 'stockcode',\n",
      "       'pos', 'neg', 'ret_1', 'label'],\n",
      "      dtype='object')\n"
     ]
    }
   ],
   "source": [
    "csi=pd.read_csv('nas_fea.csv')\n",
    "print(csi.columns)"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:25.795355300Z",
     "start_time": "2023-11-27T11:40:25.582344600Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "outputs": [],
   "source": [
    "for st in stockunique:\n",
    "    one_stock=csi[csi['stockcode']==st]\n",
    "    one_stock.to_pickle('nas90/'+st+'.pkl')"
   ],
   "metadata": {
    "collapsed": false,
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:27.038241300Z",
     "start_time": "2023-11-27T11:40:25.782922500Z"
    }
   }
  },
  {
   "cell_type": "code",
   "execution_count": 57,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:27.061622Z",
     "start_time": "2023-11-27T11:40:27.015503300Z"
    }
   },
   "outputs": [
    {
     "data": {
      "text/plain": "             date      open      high       low     close     adjcp    volume  \\\n5908   2019-03-12  0.031413  0.030800  0.032238  0.031088  0.029325  0.000069   \n5998   2019-03-13  0.032348  0.032552  0.032904  0.032709  0.030851  0.149343   \n6088   2019-03-14  0.033048  0.033935  0.033903  0.033542  0.031635  0.045569   \n6178   2019-03-15  0.034571  0.034368  0.035320  0.034515  0.032550  0.051831   \n6268   2019-03-18  0.035104  0.034442  0.035139  0.034515  0.032550  0.029321   \n...           ...       ...       ...       ...       ...       ...       ...   \n91948  2022-12-23  0.024387  0.024197  0.025037  0.024381  0.024495  0.010421   \n92038  2022-12-27  0.024648  0.024160  0.024904  0.024251  0.024366  0.008748   \n92128  2022-12-28  0.024434  0.024040  0.024685  0.023779  0.023897  0.009109   \n92218  2022-12-29  0.024256  0.024211  0.024818  0.024196  0.024311  0.009244   \n92308  2022-12-30  0.024219  0.023847  0.024552  0.024020  0.024136  0.019111   \n\n      stockcode  pos  neg     ret_1     label  \n5908       FOXA  0.5  0.5  0.375977  1.046053  \n5998       FOXA  0.5  0.5  1.046053  1.022642  \n6088       FOXA  0.5  0.5  1.022642  1.025830  \n6178       FOXA  0.5  0.5  1.025830  1.000000  \n6268       FOXA  0.5  0.5  1.000000  0.967386  \n...         ...  ...  ...       ...       ...  \n91948      FOXA  0.5  0.5  1.008525  0.995449  \n92038      FOXA  0.5  0.5  0.995449  0.983344  \n92128      FOXA  0.5  0.5  0.983344  1.014945  \n92218      FOXA  0.5  0.5  1.014945  0.993783  \n92308      FOXA  0.5  0.5  0.993783  2.333224  \n\n[961 rows x 12 columns]",
      "text/html": "<div>\n<style scoped>\n    .dataframe tbody tr th:only-of-type {\n        vertical-align: middle;\n    }\n\n    .dataframe tbody tr th {\n        vertical-align: top;\n    }\n\n    .dataframe thead th {\n        text-align: right;\n    }\n</style>\n<table border=\"1\" class=\"dataframe\">\n  <thead>\n    <tr style=\"text-align: right;\">\n      <th></th>\n      <th>date</th>\n      <th>open</th>\n      <th>high</th>\n      <th>low</th>\n      <th>close</th>\n      <th>adjcp</th>\n      <th>volume</th>\n      <th>stockcode</th>\n      <th>pos</th>\n      <th>neg</th>\n      <th>ret_1</th>\n      <th>label</th>\n    </tr>\n  </thead>\n  <tbody>\n    <tr>\n      <th>5908</th>\n      <td>2019-03-12</td>\n      <td>0.031413</td>\n      <td>0.030800</td>\n      <td>0.032238</td>\n      <td>0.031088</td>\n      <td>0.029325</td>\n      <td>0.000069</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>0.375977</td>\n      <td>1.046053</td>\n    </tr>\n    <tr>\n      <th>5998</th>\n      <td>2019-03-13</td>\n      <td>0.032348</td>\n      <td>0.032552</td>\n      <td>0.032904</td>\n      <td>0.032709</td>\n      <td>0.030851</td>\n      <td>0.149343</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>1.046053</td>\n      <td>1.022642</td>\n    </tr>\n    <tr>\n      <th>6088</th>\n      <td>2019-03-14</td>\n      <td>0.033048</td>\n      <td>0.033935</td>\n      <td>0.033903</td>\n      <td>0.033542</td>\n      <td>0.031635</td>\n      <td>0.045569</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>1.022642</td>\n      <td>1.025830</td>\n    </tr>\n    <tr>\n      <th>6178</th>\n      <td>2019-03-15</td>\n      <td>0.034571</td>\n      <td>0.034368</td>\n      <td>0.035320</td>\n      <td>0.034515</td>\n      <td>0.032550</td>\n      <td>0.051831</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>1.025830</td>\n      <td>1.000000</td>\n    </tr>\n    <tr>\n      <th>6268</th>\n      <td>2019-03-18</td>\n      <td>0.035104</td>\n      <td>0.034442</td>\n      <td>0.035139</td>\n      <td>0.034515</td>\n      <td>0.032550</td>\n      <td>0.029321</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>1.000000</td>\n      <td>0.967386</td>\n    </tr>\n    <tr>\n      <th>...</th>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n      <td>...</td>\n    </tr>\n    <tr>\n      <th>91948</th>\n      <td>2022-12-23</td>\n      <td>0.024387</td>\n      <td>0.024197</td>\n      <td>0.025037</td>\n      <td>0.024381</td>\n      <td>0.024495</td>\n      <td>0.010421</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>1.008525</td>\n      <td>0.995449</td>\n    </tr>\n    <tr>\n      <th>92038</th>\n      <td>2022-12-27</td>\n      <td>0.024648</td>\n      <td>0.024160</td>\n      <td>0.024904</td>\n      <td>0.024251</td>\n      <td>0.024366</td>\n      <td>0.008748</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>0.995449</td>\n      <td>0.983344</td>\n    </tr>\n    <tr>\n      <th>92128</th>\n      <td>2022-12-28</td>\n      <td>0.024434</td>\n      <td>0.024040</td>\n      <td>0.024685</td>\n      <td>0.023779</td>\n      <td>0.023897</td>\n      <td>0.009109</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>0.983344</td>\n      <td>1.014945</td>\n    </tr>\n    <tr>\n      <th>92218</th>\n      <td>2022-12-29</td>\n      <td>0.024256</td>\n      <td>0.024211</td>\n      <td>0.024818</td>\n      <td>0.024196</td>\n      <td>0.024311</td>\n      <td>0.009244</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>1.014945</td>\n      <td>0.993783</td>\n    </tr>\n    <tr>\n      <th>92308</th>\n      <td>2022-12-30</td>\n      <td>0.024219</td>\n      <td>0.023847</td>\n      <td>0.024552</td>\n      <td>0.024020</td>\n      <td>0.024136</td>\n      <td>0.019111</td>\n      <td>FOXA</td>\n      <td>0.5</td>\n      <td>0.5</td>\n      <td>0.993783</td>\n      <td>2.333224</td>\n    </tr>\n  </tbody>\n</table>\n<p>961 rows × 12 columns</p>\n</div>"
     },
     "execution_count": 57,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "one_stock"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 58,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:27.131285300Z",
     "start_time": "2023-11-27T11:40:27.060613400Z"
    }
   },
   "outputs": [],
   "source": [
    "return_deep=np.load('E:/baselines/deeptrader_rl/src/NAS90_output/wealth0.npy')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "ExecuteTime": {
     "end_time": "2023-11-27T11:40:27.154424400Z",
     "start_time": "2023-11-27T11:40:27.073730100Z"
    }
   },
   "outputs": [
    {
     "data": {
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     },
     "execution_count": 59,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "return_deep"
   ]
  }
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